Purpose This paper aims to study the boundary disturbance rejection control design for a flexible Timoshenko robot arm to diminish external disturbances and achieve desired angle tracking, with system vibration and elastic deformation considered. Design/methodology/approach This study introduces disturbance observer and disturbance rejection mechanism into the boundary control design for flexible Timoshenko robot arm systems. The uniform bounded stability of controlled systems is proved via Lyapunov analysis without any simplification of the infinite-dimensional system dynamics. Findings The proposed boundary disturbance rejection control scheme can effectively suppress vibrations and shear deformations, achieve the required angular positioning and reject external disturbances. Numerical simulations developed by the finite difference method are adapted to demonstrate the validity of the designed controller. Originality/value The originality of this study is to design boundary disturbance rejection control to suppress vibrations and shear deformations for the flexible Timoshenko robot arm, thereby improving the performance and control accuracy of the system.
Purpose The paper aims to propose a method to build environmental constraint region online in complex-shaped peg-in-hole assembly tasks. Design/methodology/approach Compared with conventional way which using computer-aided design (CAD) models of assembly parts to construct the environmental constraint region offline, the paper provides an online approach that consists of three aspects: modeling assembly parts through visual recognition, decomposing complex shapes into multiple primitive convex shapes and a numerical algorithm to simulate the peg-in-hole insertion contact. Besides, a contrast experiment is performed to validate the feasibility and effectiveness of the method. Findings The experiment result indicates that online construction takes less time than the offline way under the same task conditions. Furthermore, due to the CAD models of the parts are not required to be known, the method proposed in the paper has a broader application in most assembly scenarios. Originality/value With the improvement of customization and complexity of manufactured parts, the assembly of complex-shaped parts has drawn greater attention of many researchers. The assembly methods based on attractive region in environment (ARIE) have shown great performance to achieve high-precision manipulation with low-precision systems. The construction of environmental constraint region serves as an essential part of ARIE-based theory, directly affect the formulation and application of assembly strategies.
Purpose The purpose of this study is to achieve accurate matching of new process cases to historical process cases and then complete the reuse of process knowledge and assembly experience. Design/methodology/approach By integrating case-based reasoning (CBR) and ontology technology, a multilevel assembly ontology is proposed. Under the general framework, the knowledge of the assembly domain is described hierarchically and associatively. On this basis, an assembly process case matching method is developed. Findings By fully considering the influence of ontology individual, case structure, assembly scenario and introducing the correction factor, the similarity between non-correlated parts is significantly reduced. Compared with the Triple Matching-Distance Model, the degree of distinction and accuracy of parts matching are effectively improved. Finally, the usefulness of the proposed method is also proved by the matching of four practical assembly cases of precision components. Originality/value The process knowledge in historical assembly cases is expressed in a specific ontology framework, which makes up for the defects of the traditional CBR model. The proposed matching method takes into account all aspects of ontology construction and can be used well in cross-ontology similarity calculations.
PurposeThis paper aims to perform the real-time and accurate ergonomics analysis for the operator in the manual assembly, with the purpose of identifying potential ergonomic injuries when encountering labor-excessive and unreasonable assembly operations.Design/methodology/approachInstead of acquiring body data for ergonomic evaluation by arranging many observers around, this paper proposes a multi-sensor based wearable system to track worker’s posture for a continuous ergonomic assessment. Moreover, given the accurate neck postural data from the shop floor by the proposed wearable system, a continuous rapid upper limb assessment method with robustness to occasional posture changes, is proposed to evaluate the neck and upper back risk during the manual assembly operations.FindingsThe proposed method can retrieve human activity data during manual assembly operations, and experimental results illustrate that the proposed work is flexible and accurate for continuous ergonomic assessments in manual assembly operations.Originality/valueBased on the proposed multi-sensor based wearable system for posture acquisition, a real-time and high-precision ergonomics analysis is achieved with the postural data arrived continuously, it can provide a more objective indicator to assess the ergonomics during manual assembly.
Purpose This paper aims to investigate an adaptive prescribed performance control problem for switched pure-feedback non-linear systems with input quantization. Design/methodology/approach By using the semi-bounded continuous condition of non-affine functions, the controllability of the system can be guaranteed. Then, a constraint variable method is introduced to ensure that the tracking error satisfies the prescribed performance requirements. Meanwhile, to avoid the design difficulties caused by the input quantization, a non-linear decomposition method is adopted. Finally, the feasibility of the proposed control scheme is verified by a numerical simulation example. Findings Based on neural networks and prescribed performance control method, an adaptive neural control strategy for switched pure-feedback non-linear systems is proposed. Originality/value The complex deduction and non-differentiable problems of traditional prescribed performance control methods can be solved by using the proposed error transformation approach. Besides, to obtain more general results, the restrictive differentiability assumption on non-affine functions is removed.
Purpose This paper mainly aims to deal with the problems of uncertainties including modelling errors, unknown dynamics and disturbances caused by load mutation in control of permanent magnet synchronous motor (PMSM). Design/methodology/approach This paper proposes an enhanced speed sensorless vector control method based on an active disturbance rejection controller (ADRC) for a PMSM. First, a state space model of the PMSM is obtained for the field orientation control strategy. Second, a sliding mode observer (SMO) based on back electromotive force (EMF) is introduced to replace the encode to estimate the rotor flux position angle and speed. Third, an infinite impulse response (IIR) filter is introduced to eliminate high frequency noise mixed in the output of the sliding mode observer. In addition, a speed control method based on an extended state observer (ESO) is proposed to estimate and compensate for the total disturbances. Finally, an experimental set-up is built to verify the effectiveness and superiority of the proposed ADRC-based control method. Findings The comparative experimental results show that the proposed speed sensorless control method with the IIR filter can achieve excellent robustness and speed tracking performance for PMSM system. Research limitations/implications An enhanced sensorless control method based on active disturbance rejection controller is designed to realize high precision control of the PMSM; the IIR filter is used to attenuate the chattering problem of traditional SMO; this method simplifies the system and saves the total cost due to the speed sensorless technology. Practical implications The use of sensorless can reduce costs and be more beneficial to actual industrial application. Originality/value The proposed enhanced speed sensorless vector control method based on an ADRC with the IIR filter enriches the control method of PMSM. It can ameliorate system robustness and achieve excellent speed tracking performance.
Purpose Marking and inspecting are key steps in hull structure construction. However, currently most marking and inspecting operations are still carried out manually, which leads to low assembly efficiency and quality. This paper aims to solve these problems through the application of digital technology: the optical projection and machine vision. Design/methodology/approach First, the assembly process model of hull construction is established in 3D design environment. Second, the process information is presented to workers in a virtual form through optical projector, which provides accurate guidance for the manual operation. On this basis, the workers can complete welding and assembly operations readily. Finally, the machine vision method is used to check the assembly results, which can decrease the subjective errors. Findings A rapid and accurate assembly positioning for hull structure construction is realized based on optical projection, which can avoid the pollution caused by the marking machine and the error caused by human. Originality/value This paper combines the advantages of optical projection and machine vision to the field of shipbuilding. The shortcomings of the traditional marking and inspection methods is effectively solved, which may provide a new way for enhancing the assembly efficiency and quality.
Purpose This paper aims to develop a method to improve the accuracy of tolerance analysis considering the spatial distribution characteristics of part surface morphology (SDCPSM) and local surface deformations (LSD) of planar mating surfaces during the assembly process. Design/methodology/approach First, this paper proposes a skin modeling method considering SDCPSM based on Non-Gaussian random field. Second, based on the skin model shapes, an improved boundary element method is adopted to solve LSD of nonideal planar mating surfaces, and the progressive contact method is adopted to obtain relative positioning deviation of mating surfaces. Finally, the case study is given to verify the proposed approach. Findings Through the case study, the results show that different SDCPSM have different influences on tolerance analysis, and LSD have nonnegligible and different influence on tolerance analysis considering different SDCPSM. In addition, the LSD have a greater influence on translational deviation along the z -axis than rotational deviation around the x - and y -axes. Originality/value The surface morphology with different spatial distribution characteristics leads to different contact behavior of planar mating surfaces, especially when considering the LSD of mating surfaces during the assembly process, which will have further influence on tolerance analysis. To address the above problem, this paper proposes a tolerance analysis method with skin modeling considering SDCPSM and LSD of mating surfaces, which can help to improve the accuracy of tolerance analysis.
Purpose Due to the advantages of fast response, high positioning precision and large stiffness, the piezoelectric-actuated nanopositioning stage is widely used in the micro/nanomachining fields. However, due to the inherent nonlinear hysteresis of the piezoelectric-actuator, the positioning accuracy of nanopositioning stage is greatly degraded. Besides, the nanopositioning stage is always performed with repetitive trajectories as the reference signals in applications, which makes the hysteresis behavior periodic. To this end, an adaptive resonance suppression iterative learning control (ARS-ILC) is proposed to address the hysteresis effect. With this effort, the positioning accuracy of the nanopositioning stage is improved. Design/methodology/approach The hysteresis behavior is identified by the Prandtl–Ishlinskii model. By establishing a convergence function, it is demonstrated that the learnable band of ILC is restricted by the lightly damping resonance of nanopositioning stage. Then, an adaptive notch filter (ANF) with constrained poles and zeros is adopted to suppress the resonant peak. Finally, online stability supervision (OSS) is used to ensure that the estimated frequency converges to the resonant frequency. Findings A series of experiments were carried out in the nanopositioning stage, and the results validated that the OSS is available to ensure the convergence of the ANF. Furthermore, the learnable band was extended via ARS-ILC; thus, the hysteresis behavior of nanopositioning stage has been canceled. Originality/value Due to high accuracy and easy implementation, the ARS-ILC can be used in not only nanopositioning stage control but other fabrication process control with repetitive motion.
PurposeThis paper aims to propose a method to automate the tolerance analyses of mechanical assembly using STandard for the Exchange of Product model data-Application Protocol Part 242 (STEP AP 242) files derived from the 3-D computer-aided design (CAD) models. Design/methodology/approachProduct manufacturing information and mating information available in ISO 10303 STEP AP242 files resulting from the 3-D CAD model of mechanical assembly are extracted. The extracted geometric attributes, geometric dimensioning and tolerancing (GD&T) and mating information are used to automatically generate assembly graph and mating edges required for the tolerance analyses of the mechanical assembly by using the matrix approach. FindingsThe feasibility of the proposed method is verified through two mechanical assembly case studies. The results of manual calculations and tolerance values computed by the automated method are very closely matching. Practical implicationsTolerance analysis is an integral part of product development that directly influences the cost and performance of a product. Apart from the academic interest, the work is expected to have positive implications for the digital design and smart manufacturing industry that involve in the development of solutions for automation of design and manufacturing system functions. Originality/valueThe approach presented in the paper that aids the automation of tolerance analyses of mechanical assembly is an innovative application of the STEP AP 242 file. The automation of tolerance analyses would improve the productivity and efficiency of the product realization process.
Purpose The purpose of this paper is to develop a human activity-aware adaptive shared control solution for human–robot interaction in surgical operation. Hands-on control and teleoperation are two main procedures switched frequently in teleoperated minimally invasive surgery (MIS). The detailed human activity in the procedures can be defined and recognized using the sensor information. In this paper, a novel continuous adaptive shared control method is proposed for manipulators with Cartesian impedance control in the surgical scenario. Design/methodology/approach A human activity-aware shared control solution by adjusting the weight function is introduced to achieve smooth transition among different human activities, including hands-on control and teleoperation. Instead of introducing various controllers and switching among them during the surgical procedures, the proposed solution integrated all the human activity-based controllers into a single controller and the transition among the procedures is smooth and stable. The effectiveness of the proposed control approach was verified in a lab setup environment. The results prove that the robot behavior is stable and smooth. The algorithm is feasible and can achieve a human activity-aware adaptive shared control solution for human–robot interaction in surgical operation. Findings Based on the experiment, the results confirm that the proposed human activity-aware adaptive shared control solution can switch the device behavior automatically using the real-time sensor information. The transition between different activities is smooth and stable. Practical implications For teleoperated surgical applications, the proposed method integrated different controllers for various human activities into a single controller by recognizing the activities using the real-time sensor information and the transition between different procedures is smooth and stable. It eases the surgical work for the surgeon and enhances the safety during the transition of control modes. The presented scheme provides a general solution to address the switching of working procedures in teleoperated MIS. Originality/value To the best of the authors’ knowledge, this paper is the first to propose human activity-aware adaptive shared control solution for human–robot interaction in surgical operations.
Purpose This paper aims to provide a novel integrated fault detection method for industrial process monitoring. Design/methodology/approach A novel integrated fault detection method based on the combination of Mallat (MA) algorithm, weight-elimination (WE) algorithm, conjugate gradient (CG) algorithm and multi-dimensional Taylor network (MTN) dynamic model, namely, MA-WE-CG-MTN, is proposed in this paper. First, MA algorithm is taken as data pre-processing. Second, in virtue of approximation ability and low computation complexity owing to the simple structure of MTN, MTN dynamic models are constructed for each frequency band. Furthermore, the CG algorithm is used to discipline the model parameters and the outputs of MTN model of each frequency band are gained. Third, the authors introduce the WE algorithm to cut down the number of middle layer nodes of MTN, reducing the complexity of the network. Finally, the outputs of MTN model for each frequency band are superimposed to achieve outputs of MTN model, and fault detection is proceeded by the residual error generator based on the difference between the output of MTN model and the actual output. Findings The novel proposed method is used to perform fault detection for industrial process monitoring effectively, such as the Benchmark Simulation Model 1 wastewater treatment process. Originality/value The novel proposed method has generality and provides considerably improved performance and effectiveness, which is used to perform fault detection for industrial process monitoring. The proposed method has good robustness, low complexity and easy implementation.
Purpose This paper aims to present a novel transfer alignment method based on combined double-time observations with velocity and attitude for ships' poor maneuverability to address the system errors introduced by flexural deformation and installing which are difficult to calibrate. Design/methodology/approach Based on velocity and attitude matching, redesigning and deducing Kalman filter model by combining double-time observation. By introducing the sampling of the previous update cycle of the strapdown inertial navigation system (SINS), current observation subtracts previous observation are used as measurements for transfer alignment filter, system error in measurement introduced by deformation and installing can be effectively removed. Findings The results of simulations and turntable tests show that when there is a system error, the proposed method can improve alignment accuracy, shorten the alignment process and not require any active maneuvers or additional sensor equipment. Originality/value Calibrating those deformations and installing errors during transfer alignment need special maneuvers along different axes, which is difficult to fulfill for ships' poor maneuverability. Without additional sensor equipment and active maneuvers, the system errors in attitude measurement can be eliminated by the proposed algorithms, meanwhile improving the accuracy of the shipboard SINS transfer alignment.
Purpose Assembly errors of aeroengine rotor must be controlled to improve the aeroengine efficiency. However, current method cannot truly reflect assembly errors of the rotor in working state owing to difficulties in error analysis. Therefore, the purpose of this study is to establish an optimization method for aeroengine rotor stacking assembly. Design/methodology/approach The assembly structure of aeroengine rotor is featured. Rotor eccentricity is optimized based on Jacobian–Torsor model. Then, an optimization method for assembly work is proposed. The assembly process of the high-pressure compressor rotor and the high-pressure turbine rotor as the rotor core assembly is mainly considered. Findings An aeroengine rotor is assembled to verify the method. The results show that the predicted eccentricity differed from the measured eccentricity by 6.1%, with a comprehensive error of 8.1%. Thus, the optimization method has certain significance for rotor assembly error analysis and assembly process optimization. Originality/value In view of the error analysis in the stacking assembly of aeroengine rotor, an innovative optimization method is proposed. The method provides a novel approach for the aeroengine rotor assembly optimization and is applicable for the assembly of high-pressure compressor rotor and high-pressure turbine rotor as the rotor core assembly.
Purpose This paper aims to provide a precise tracking control scheme for multi-input multi-output "MIMO" nonlinear systems with unknown input time-delay in industrial process. Design/methodology/approach The predictive control scheme based on multi-dimensional Taylor network (MTN) model is proposed. First, for the unknown input time-delay, the cross-correlation function is used to identify the input time-delay through just the input and output data. And then, the scheme of predictive control is designed based on the MTN model. It goes as follows: a recursive d-step-ahead MTN predictive model is developed to compensate the influence of time-delay, and the extended Kalman filter (EKF) algorithm is applied for its learning; the multistep predictive objective function is designed, and the optimal controlled output is determined by iterative refinement; and the convergence of MTN predictive model and the stability of closed-loop system are proved. Findings Simulation results show that the proposed scheme is of desirable generality and capable of performing the tracking control for MIMO nonlinear systems with unknown input time-delay in industrial process effectively, such as the continuous stirred tank reactor (CSTR) process, which provides a considerably improved performance and effectiveness. The proposed scheme promises strong robustness, low complexity and easy implementation. Research limitations/implications For the limitations of proposed scheme, the time-invariant time-delay is only considered in time-delay identification and control schemes. And the CSTR process is only introduced to prove that the proposed scheme can adapt to practical industrial scenario. Originality/value The originality of the paper is that the proposed MTN control scheme has good tracking performance, which solves the influence of time-delay, coupling and nonlinearity and the real-time performance for MIMO nonlinear systems with unknown input time-delay.
Purpose The purpose of this paper is to propose a approach for data visualization and industrial process monitoring. Design/methodology/approach A deep enhanced t-distributed stochastic neighbor embedding (DESNE) neural network is proposed for data visualization and process monitoring. The DESNE is composed of two deep neural networks: stacked variant auto-encoder (SVAE) and a deep label-guided t-stochastic neighbor embedding (DLSNE) neural network. In the DESNE network, SVAE extracts informative features of the raw data set, and then DLSNE projects the extracted features to a two dimensional graph. Findings The proposed DESNE is verified on the Tennessee Eastman process and a real data set of blade icing of wind turbines. The results indicate that DESNE outperforms some visualization methods in process monitoring. Originality/value This paper has significant originality. A stacked variant auto-encoder is proposed for feature extraction. The stacked variant auto-encoder can improve the separation among classes. A deep label-guided t-SNE is proposed for visualization. A novel visualization-based process monitoring method is proposed.
PurposeA welding robot is a complicated system with uncertainty, time-varying, strong coupling and non-linear system. It is more complicated if it is used in an underwater environment. It is difficult to establish an accurate dynamic model for an underwater welding robot. Aiming at the tracking control of an underwater welding robot, it is difficult to achieve the control performance requirements by the classical proportional integral derivative control method to realize automatic tracking of the seam. The purpose of this paper is to suggest a novel method to deal with these issues.Design/methodology/approachTo combine the advantages of active disturbance rejection control (ADRC) and sliding mode control (SMC) to improve the shortcomings of a single control method, a hybrid control method for an underwater welding robot trajectory tracking based on SMC_ADRC is proposed in this research work.FindingsThe simulation experiment of the proposed approach is carried out by Matlab/Simulink, and the welding experiment is recorded. The seam gets plumper and smoother, with better continuity and no undercut phenomenon.Originality/valueThe proposed approach is effective and reliable, and the system’s tracking performance is stable, which can effectively reduce chattering and improve system robustness.
Purpose Quality management systems are commonly applied to meet the increasingly stringent requirements for product quality in discrete manufacturing industries. However, traditional experience-driven quality management methods are incapable of handling heterogeneous data from multiple sources, leading to information islands. This study aims to present a quality management key performance indicator visualization (QM-KPIVIS) system to enable integrated quality control and ultimately ensure product quality. Design/methodology/approach Based on multiple heterogeneous data, an integrated approach is proposed to quantify explicitly the relationship between Internet of Things data and product quality. Specifically, this study identifies the tracing path of quality problems based on multiple heterogeneous quality information tree. In addition, a hierarchical analysis approach is adopted to calculate the key performance indicators of quality influencing factors in the quality control process. Findings Proposed QM-KPIVIS system consists of data visualization, quality problem processing, quality optimization and user rights management modules, which perform in a well-coordinated manner. An empirical study was also conducted to validate the effectiveness of proposed system. Originality/value To the best of the authors’ knowledge, this study is the first attempt to use industrial Internet of Things and multisource heterogeneous data for integrated product quality management. Proposed approach is more user-friendly and intuitive compared to traditional empirically driven quality management methods and has been initially applied in the manufacturing industry.
Purpose Embroidery as a textile embellishment technique plays an important role in people's daily life. Esthetic embroidery artworks possess cultural values. With the development of robotics and artificial intelligence (AI), these technologies have been studied and applied in the embroidery process. This study aims to survey how these technologies facilitate embroidery from different aspects. Design/methodology/approach This paper surveys how the technologies of robotics and AI are applied in the embroidery field. The applications are mainly reviewed from three aspects: computerized robotic embroidery systems has been widely used for the mass production of embroidered textiles, the advanced technological systems and techniques have greatly facilitated the development of smart textiles and the artificial intelligence plays an important role in the inheritance, innovation and protection of traditional handicraft artwork of embroidery. Findings The programmable robotic embroidery machines have greatly improved the production efficiency of embroidered textiles and promoted the development of electronic textiles. The AI, mainly the deep learning technology, brings significant benefits to esthetic embroidery creation. Technology-based embroidery has become a hot research topic in the field of textiles. Originality/value This paper summarizes the application of robotics and AI technologies in the field of embroidery, which provides readers a comprehensive and systematic understanding about the research progress of modern technology-oriented embroidery. This helps readers gain inspiration from the technology perspectives.
Purpose Aiming at the problem that the transmission mechanism of the assembly error of the multi-stage rotor with saddle surface type is not clear, the purpose of this paper is to propose a deep belief network to realize the prediction of the coaxiality and perpendicularity of the multi-stage rotor. Design/methodology/approach First, the surface type of the aero-engine rotor is classified. The rotor surface profile sampling data is converted into image structure data, and a rotor surface type classifier based on convolutional neural network is established. Then, for the saddle surface rotor, a prediction model of coaxiality and perpendicularity based on deep belief network is established. To verify the effectiveness of the coaxiality and perpendicularity prediction method proposed in this paper, a multi-stage rotor coaxiality and perpendicularity assembly measurement experiment is carried out. Findings The results of this paper show that the accuracy rate of face type classification using convolutional neural network is 99%, which meets the requirements of subsequent assembly process. For the 80 sets of test samples, the average errors of the coaxiality and perpendicularity of the deep belief network prediction method are 0.1 and 1.6 µm, respectively. Originality/value Therefore, the method proposed in this paper can be used not only for rotor surface classification but also to guide the assembly of aero-engine multi-stage rotors.
